Philips’ public-private partnership COMBINE-CT consortium has received a $6.5-million-euro grant ($7 million U.S.) from the Innovative Health Initiative (IHI).
The consortium will use the grant to investigate the use of CT to improve diagnosis and treatment outcomes of coronary artery disease (CAD) in Europe, according to the firm.
The goals of COMBINE-CT include increasing the use of coronary computed tomography angiography; opening data silos between hospital departments involved in the care of CAD patients; and simplifying and improving workflow for physicians, nurses, and technologists. It includes Philips, the Université Lyon 1 Claude Bernard and its affiliate entity Hospices Civils De Lyon, Instituto de Investigación Biomédica de Salamanca (IBSAL), Amsterdam UMC location AMC, University Clinic Cologne, Medical Research Infrastructure Development and Health Services Fund by the Sheba Medical Center, Cardiologie Centra Nederland, Novo Nordisk, Consorcio Centro de Investigacion Biomedica en Red M.P. & EUPATI Foundation, according to the company.
The IHI is a partnership between the European Union and industry associations, among them the European Trade Association group COCIR (medical imaging, radiotherapy, health ICT, and electromedical industries) and MedTech Europe.
![Images show the pectoralis muscles of a healthy male individual who never smoked (age, 66 years; height, 178 cm; body mass index [BMI, calculated as weight in kilograms divided by height in meters squared], 28.4; number of cigarette pack-years, 0; forced expiratory volume in 1 second [FEV1], 97.6% predicted; FEV1: forced vital capacity [FVC] ratio, 0.71; pectoralis muscle area [PMA], 59.4 cm2; pectoralis muscle volume [PMV], 764 cm3) and a male individual with a smoking history and chronic obstructive pulmonary disorder (COPD) (age, 66 years; height, 178 cm; BMI, 27.5; number of cigarette pack-years, 43.2, FEV1, 48% predicted; FEV1:FVC, 0.56; PMA, 35 cm2; PMV, 480.8 cm3) from the Canadian Cohort Obstructive Lung Disease (i.e., CanCOLD) study. The CT image is shown in the axial plane. The PMV is automatically extracted using the developed deep learning model and overlayed onto the lungs for visual clarity.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/03/genkin.25LqljVF0y.jpg?auto=format%2Ccompress&crop=focalpoint&dpr=2&fit=crop&h=167&q=70&w=250)
